Without a shadow of a doubt, the most exciting application of machine learning has been in autonomous vehicles. The technology needed is far more complex than we could have predicted and a large variety of components are required for us to achieve fully autonomous vehicles. This is where some impressive new startups have broken into the industry, bringing their takes on how the technology should be applied and developed. Joining us at the Deep Learning Summit in San Francisco this month is Ouster, we had the opportunity to chat with Reyhaneh Kazerani, Machine Learning Engineer at Ouster. She gave us great insight into the exciting computer vision projects at Ouster and her perspective on future machine learning developments.

In Christmas movies that have been released in recent years, Santa has upped his game bringing kids games consoles, laptops and all sorts, but his sleigh hasn’t seemed to quite match the times! This is all about to change with the JNGL64 - an autonomous sleigh to help Santa on his way this Christmas eve.
‘[Santa] can choose from four vanity license plates, five shades of red, and whether the vehicle has treads or skis. There’s even a variety of hood ornaments, including a reindeer, angel, snowman, and decorated Christmas tree.’

How do you go about transforming a 100+ year old auto company with over 120,000 employees from their traditional methods into the digital, artificially intelligent way of thinking?
This is the challenge Renault are currently facing, and one that led to the launch of Renault Digital that started its operations on January 1st of this year and is aimed at digitalising Renault ‘s core business for it’s employees, partners and clients worldwide, working to build tomorrow’s digital abilities and scope.

In previous years, calling a cab could be a bit of a pain. You needed to make sure you had cash, allowed enough time for the driver to arrive, had the number of the cheapest taxi firm, and made sure you asked for it to go on the meter so you weren’t overcharged. If you’re switched on and haven’t been living under a rock for the past few years you probably haven’t had this problem for quite some time thanks to Uber.

‘We hear about self-drive cars all the time, but you know what’s really cool, autonomy for aircraft!’ Electric aircrafts that are currently in circulation have ‘a fantastic property in that they’re quieter than helicopters, but can still land in the same space’. These electric machines, however, they still require a pilot, ‘so what do we do? We make them autonomous.’ Human error is the biggest cause of aviation accidents, so Airbus concluded that ‘electrically operated aerial vehicles combined with more autonomous features are far safer’ than human operated planes.
‘Whilst drones are reaching higher levels of autonomy than aircrafts, they aren’t built to the same autonomy as personal aircrafts. Occasionally drones fall out of the sky - reliability and safety levels are far below what would be considered acceptable for human transport.’

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. Thanks to the global popularity of apps like Lyft and Uber, there are now hundreds of thousands of ride-share drivers, millions of users and billions in VC funding for apps and companies in the industry, despite the dominating companies being only 4-5 years old. But how will autonomous vehicles fit into real-time high-capacity ridesharing?

As part of a five year collaboration project, Toyota Research are working with MIT’s Media Lab to build and analyse new deep-learning based perception and motion based planning technologies for autonomous vehicles. Toyota are working with a series of companies specialising in blockchain technology (a distributed database used to maintain a continuously growing list of records that powers the cryptocurrency bitcoin) and are aiming to explore how this can be applied to the industry.

Our last events before the summer Machine Intelligence Summit, and Machine Intelligence in Autonomous Vehicles Summit are almost upon us, and we are please to be able to offer the chance of winning a complimentary ticket to anyone who recommends 2 inspirational people working in AI. This could be a student, founder of a cutting-edge startup, academic working on a research paper, or an industry expert who would benefit from becoming part of the RE•WORK community, presenting their work or attending a RE•WORK event.
Recommend experts here to be in with the chance of attending Amsterdam Summits June 28 & 29th for free.

The question of whether technology will improve or further disrupt urban traffic remains, and will so until driverless cars are in mainstream operation, but autonomous vehicle testing and intelligence is rapidly advancing. Ahead of our Machine Intelligence in Autonomous Vehicle Summit in Amsterdam 28 & 29 June, we’re taking a look at the most recent breakthroughs and news in this space.
Currently, all self-drive cars in testing are required to have a human backup driver in case of emergencies, but Delphi and Transdev have revealed that they are planning to use autonomous taxis and shuttles to carry passengers on roads in France.

Offering increased productivity, accessibility, efficiency, a more positive impact on the environment, and the potential for additional safety, autonomous vehicles are widely regarded as the future of urban transportation. But how can self-driving cars and other forms of autonomous transport be seamlessly integrated into existing cities' infrastructure and environments?

In the world of intelligent machines, perception answers the question: what is around me? This situational awareness is paramount for safe operation of autonomous vehicles in real-world environments. Michael Milford, Associate Professor at Queensland University of Technology (QUT), gives insight into the recent advancements in robotic perception in autonomous systems and the challenges that lie ahead.

Congested traffic in cities and drivers searching suitable parking spots is a massive problem that must be addressed if we are to successfully combat climate change and meet sustainable development goals. Mathias Bürki, PhD Candidate in the Autonomous Systems Lab at ETH Zurich, discusses bringing fully autonomous driving into urban environments, and visual localization and mapping systems in the context of autonomous driving.